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Optimal H∞ state feedback sampled-data control applied to Markov jump linear systems | IEEE Conference Publication | IEEE Xplore

Optimal H∞ state feedback sampled-data control applied to Markov jump linear systems


Abstract:

This paper is entirely devoted to analyse the optimal H∞ state feedback sampled-data control design problem for continuous-time Markov jump linear systems. In the framewo...Show More

Abstract:

This paper is entirely devoted to analyse the optimal H state feedback sampled-data control design problem for continuous-time Markov jump linear systems. In the framework of this problem, the original system is rewritten in a more general formulation, called Hybrid Markov jump linear system. In this new context, closed-loop mean square stability and H performance are fully characterized by means of necessary and sufficient conditions in terms of coupled differential Riccati equations. These conditions are adapted to provide optimal sampled-data control in terms of a convex programming problem expressed by linear matrix inequalities. An iterative globally convergent algorithm to implement the proposed solution that encloses the H2 problem is also provided. A numerical example illustrates the theory.
Date of Conference: 29 June 2016 - 01 July 2016
Date Added to IEEE Xplore: 09 January 2017
ISBN Information:
Conference Location: Aalborg, Denmark

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